Full-Time Statistician

• Conduct statistical analyses on datasets including environmental and safety assessment studies such as agronomic/phenotypic, composition, germination, non-target organism, and protein expression.
• Provide guidance on experimental design in support of robust data analysis for studies to support Trait Evaluation and Product Safety.
• Assist in interpretation of results and generating reports including the production of data tables and graphics for data visualization.
• Collaborate directly with applied crop teams, study directors and other scientists, engaging stakeholders and experts across Traits R&D.

• Master’s degree statistics, preferably in biostatistics, agriculture sciences and/or related sciences.
• A minimum 2 years of experience in experimental design, statistical analysis and applied statistics.
• Experience utilizing SAS statistical software for the analysis of experimental datasets.
• Must be eligible to work in the United States without sponsorship support from Syngenta.

• Proficient skills in Data Analytics and Experimental Design especially as it pertains to field trialing, agronomy, and crop composition.
• Ability to perform statistical analysis of data for the purpose of making data-driven decisions and understand the complexity of statistical analysis within agricultural research.
• Proficient understanding of experimental designs commonly used in agriculture and life sciences.
• Strong experience collaborating with diverse teams to make data-driven decisions.
• Strong oral and written communication skills in English, including the ability to communicate effectively with individuals of diverse language, cultural, and scientific backgrounds.
• Proficiency in data organization, analysis and reporting utilizing programs such as R or Python.
• Proficient in statistical analysis with strong focus in mixed models and multivariate analyses.
• Understanding of experimental design, knowledge in field trialing, and data analysis of data derived from field experiments in agriculture.
• Experience conducting sample size and power calculations appropriate for hypothesis testing.
• Understanding of Good Laboratory Practices (GLP) and ability to comply with GLP requirements.

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